Devitechs is seeking a professional in the Town of Texas, Wisconsin, to design, develop, and deploy scalable machine learning models. Responsibilities include collaborating across teams, optimizing models, utilizing cloud platforms for deployments, and troubleshooting performance issues. The ideal candidate should have experience in data science and machine learning technologies. A strong emphasis on automation and ensuring data quality in AI workflows is required for this role.
Responsibilities
Design, develop, and deploy scalable machine learning models.
Work on data preprocessing, feature engineering, and model optimization.
Build and implement advanced algorithms like deep learning and NLP.
Collaborate with teams to deliver AI-driven solutions.
Integrate machine learning models into production environments.
Monitor and improve model performance using metrics.
Handle large datasets and distributed computing frameworks.
Implement automation for model training and deployment.
Ensure data quality and integrity across AI workflows.
Research the latest advancements in AI and data science.
Utilize cloud platforms for model deployment.
Develop APIs for machine learning functionalities.
Troubleshoot technical issues related to models.
Document processes and system designs.
Contribute to innovation by identifying new AI opportunities.
Job description
Responsibilities
Design, develop, and deploy scalable machine learning models to solve real-world business problems and improve decision‑making processes
Work extensively on data preprocessing, feature engineering, and model optimization to enhance performance and accuracy
Build and implement advanced algorithms including deep learning, NLP, and predictive analytics solutions
Collaborate with cross‑functional teams including data scientists, engineers, and product managers to deliver AI‑driven solutions
Integrate machine learning models into production environments and ensure smooth deployment pipelines
Monitor, evaluate, and continuously improve model performance using appropriate metrics and feedback loops
Work with large datasets and distributed computing frameworks to handle complex data challenges efficiently
Implement automation processes to streamline model training, testing, and deployment
Ensure data quality, integrity, and governance standards are maintained across all AI workflows
Research and stay updated with the latest advancements in AI, ML, and data science technologies
Utilize cloud platforms such as AWS, Azure, or GCP for model deployment and scalability
Develop APIs and services to expose machine learning functionalities to other applications
Troubleshoot and resolve technical issues related to model performance and deployment
Document processes, methodologies, and system designs for future reference and scalability
Contribute to innovation by identifying new AI opportunities within the organization